Gender Bias Impacts Top-Merited Candidates.
Gender Bias Impacts Top-Merited Candidates.
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DOI：
10.3389/frma.2021.594424
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发表时间：
2021
影响因子：
--
通讯作者：
Hägg S
中科院分区：
文献类型：
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作者：
Andersson ER;Hagberg CE;Hägg S
对公平竞争的期望是学术界是精英政治这一假设的基础。然而，偏见可能会加剧同行评审过程中的性别不平等，不公平地淘汰杰出个人。在这里，我们询问申请人的性别是否会对性别平等排名最高的国家的同行评审产生偏见。我们分析了瑞典医科大学卡罗林斯卡学院 (KI) 连续四年（2014 年至 2017 年）助理教授 (n = 207) 和高级研究员 (n = 153) 招聘资助的同行评审评估。我们得出了综合文献计量分数来量化申请人的生产力，并将该分数与申请人优点的主观外部（非 KI）同行评审员分数进行比较，以分别测试其与男性和女性的关联。为了确定研究领域是否存在性别隔离，我们分析了出版物列表中男性和女性的 MeSH 术语，并分析了它们的重叠。 MeSH 主题不存在性别隔离，但评审员对具有同等优点的男性和女性的评分却不平等。男性收到的外部评审分数导致计算出的生产力和主观外部评审分数之间的关联性更强（更陡的斜率），这意味着同行评审人员会根据相应的绩效分数“奖励”男性的生产力。然而，每增加一个综合文献计量分，申请助理教授或高级研究员的女性得分仅为男性的 32% 或 92%。随着生产力的提高，男性和女性之间的绩效分数差异也在增加。因此，性别偏见的累积是可以量化的，并会影响最高层的竞争，即最终选出成功候选人的人才库。可以计算跟踪记录，因此资助组织可以实施计算的跟踪记录作为质量控制，以评估偏见是否影响审稿人的评估。
Expectations of fair competition underlie the assumption that academia is a meritocracy. However, bias may reinforce gender inequality in peer review processes, unfairly eliminating outstanding individuals. Here, we ask whether applicant gender biases peer review in a country top ranked for gender equality. We analyzed peer review assessments for recruitment grants at a Swedish medical university, Karolinska Institutet (KI), during four consecutive years (2014–2017) for Assistant Professor (n = 207) and Senior Researcher (n = 153). We derived a composite bibliometric score to quantify applicant productivity and compared this score with subjective external (non-KI) peer reviewer scores of applicants' merits to test their association for men and women, separately. To determine whether there was gender segregation in research fields, we analyzed publication list MeSH terms, for men and women, and analyzed their overlap. There was no gendered MeSH topic segregation, yet men and women with equal merits are scored unequally by reviewers. Men receive external reviewer scores resulting in stronger associations (steeper slopes) between computed productivity and subjective external reviewer scores, meaning that peer reviewers “reward” men's productivity with proportional merit scores. However, women applying for assistant professor or senior researcher receive only 32 or 92% of the score men receive, respectively, for each additional composite bibliometric score point. As productivity increases, the differences in merit scores between men and women increases. Accumulating gender bias is thus quantifiable and impacts the highest tier of competition, the pool from which successful candidates are ultimately chosen. Track record can be computed, and granting organizations could therefore implement a computed track record as quality control to assess whether bias affects reviewer assessments.